code: def test_warpped_model_script_detection(self):
      class WrappedDETR(nn.Module):
          def __init__(self, model):
              super().__init__()
              self.model = model
  
          def forward(self, inputs: List[Tensor]):
              sample = nested_tensor_from_tensor_list(inputs)
              return self.model(sample)
  
      model = detr_resnet50(pretrained=False)
      wrapped_model = WrappedDETR(model)
      wrapped_model.eval()
      scripted_model = torch.jit.script(wrapped_model)
      x = [torch.rand(3, 200, 200), torch.rand(3, 200, 250)]
      out = wrapped_model(x)
      out_script = scripted_model(x)
      self.assertTrue(
          out["pred_logits"].equal(out_script["pred_logits"])
      )
      self.assertTrue(out["pred_boxes"].equal(out_script["pred_boxes"]))
  
imports: import io
  import unittest
  import torch
  from torch import nn, Tensor
  from typing import List
  from models.matcher import HungarianMatcher
  from models.position_encoding import PositionEmbeddingSine, PositionEmbeddingLearned
  from models.backbone import Backbone, Joiner, BackboneBase
  from util import box_ops
  from util.misc import nested_tensor_from_tensor_list
  from hubconf import detr_resnet50, detr_resnet50_panoptic
label_desc: Use image node_id 9 for calling the Tester obj's underlying member method code with example usage: obj.test_warpped_model_script_detection() and returns: self